English

Brain reaction times: Linking individual and collective behaviour through Physics modelling

Biological Physics 2019-11-20 v2 Physics and Society Neurons and Cognition

Abstract

An individual's reaction time data to visual stimuli have usually been represented in Experimental Psychology by means of an ex-Gaussian function (EGF). In most previous works, researchers have mainly aimed at finding a meaning for the parameters of the EGF function in relation to psychological phenomena. We will focus on interpreting the reaction times (RTs) of a group of individuals rather than a single person's RT, which is relevant for the different contexts of social sciences. In doing so, the same model as for the Ideal Gases (IG) (an inanimate system of non-interacting particles) emerges from the experimental RT data. Both systems are characterised by a collective parameter which is k_BT in the case of the system of particles and what we have called life span parameter for the system of brains. Similarly, we came across a Maxwell-Boltzmann-type distribution for the system of brains which provides a natural and more complete characterisation of the collective time response than has ever been provided before. Thus, we are able to know about the behaviour of a single individual in relation to the coetaneous group to which they belong and through the application of a physical law. This leads to a new entropy-based methodology for the classification of the individuals forming the system which emerges from the physical law governing the system of brains. To the best of our knowledge, this is the first work in the literature reporting on the emergence of a physical theory (IG) from human RT experimental data.

Cite

@article{arxiv.1910.12725,
  title  = {Brain reaction times: Linking individual and collective behaviour through Physics modelling},
  author = {Juan Carlos Castro-Palacio and Pedro Fernández de Córdoba and J. M. Isidro and Esperanza Navarro-Pardo},
  journal= {arXiv preprint arXiv:1910.12725},
  year   = {2019}
}

Comments

16 pages and 3 figures

R2 v1 2026-06-23T11:57:15.609Z